{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--BOOK_INFORMATION-->\n",
    "<img align=\"left\" style=\"padding-right:10px;\" src=\"figures/PHydro-cover-small.png\">\n",
    "*This is the Jupyter notebook version of the [Python in Hydrology](http://www.greenteapress.com/pythonhydro/pythonhydro.html) by Sat Kumar Tomer.*\n",
    "*Source code is available at [code.google.com](https://code.google.com/archive/p/python-in-hydrology/source).*\n",
    "\n",
    "*The book is available under the [GNU Free Documentation License](http://www.gnu.org/copyleft/fdl.html). If you have comments, corrections or suggestions, please send email to satkumartomer@gmail.com.*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<!--NAVIGATION-->\n",
    "< [Q-Q Plot](07.07-Q-Q-Plot.ipynb) | [Contents](Index.ipynb) | [Annotation](07.09-Annotation.ipynb) >"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 7.8 plotyy\n",
    "\n",
    "如果我们想要绘制两个有不同范围的变量(最大和最小)在相同的图形中，我们就不能用相同的坐标轴绘制它们。如果我们这样做了，我们将无法看到一个变量的变化。图7.11显示了具有两个y轴的图形。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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ly6BMGef2V6IEzJwJu3bBK6/c9/ZvJ35j1/ldPN3oaZdmiM0qYxqPITYhlunh03VLMSRjDEVqVK4Ms2bBjh0wZsxdKRRm757NzbibjG44WqPAjOPp7snTjZ7m5yM/s/fCXt1ycj5SwsiRsHmzuoYaNnRNv507w/PPq4CMpUvveuvrP7+mgHcBBtYa6Bot2aR2sdq0KNuCCdsmGJepRTCG4kF07QpvvAHTp8O33wJqCj9x20TqFa9Ho5KNNAvMOKMajMLbw5svtnyhW0rOZ/FimDMH3n5bLTK7kvffh3r14PHH4fRpQCX/WxSxiJC6Ifh6+bpWTzYY02gMR64eMS5Ti2AMRVq8+SZ07KiiVnbuZOvprew8v5MnGzxpiyl8CoV9CjO09lC+2/Wd8fs6k5s3VQhsnTrwmoas0HnywLx5cPs2DB4MiYlM3j6ZxKREnmr0lOv1ZIMegT0onq84X239SrcUA8ZQpI27u3If5M8PzzzDxG0TyOeVzzZT+Dt5tsmzxCbEMnn7ZN1Sci7jx6tMsBMmgIemLMJVq8JXX8GGDSS8+w6Ttk+iU5VOVC5UWY+eLOLl7sWTDZ5k1aFVHL5yWLecXI8xFOlRuDC88w5s3Eji3DkMrjUYvzxOimBxIjUeqkG7iu2YtH2S8fs6g1274LPPVGrwhx/Wq2XYMBg4ELe33qLYwXOMaTRGr54sMqrBKNzd3JmwbYJuKbkeIe9YqLU6vr6+Mjo62vUdJyZyoXp5bp87xdW/fqd2Rc03giwyZ/ccBoUOYsOwDbQq30q3nJxDUhI88ggcOgT790OhQroVQVQUUWWKsq+EB03338TNgtkDMkLfBX1Zc2QNp/55Ch9PH91ysoQQIkZKaZ8FolQwM4oMIN3c+GcXd8pch9rTV+qWk2WCA4Lx8/Jj5s6Z6X/YkHGmTlUFhj76yBpGAtgZe5w3WiTQ7GAsbj/ad0F4TKMxXI29yrw983RLydUYQ5EBNp7YyGz/4xzp2AQ+/BCOHtUtKUv4ePrQp3ofFuxbQEx8jG45OYOLF+HVV6FVKxhinQ2YM3fOZGpjDxIrV4KXX4aEBN2SskTLci2pUbSGWVvTjDEUGWDitokU8C5AiW++VwvcL76oW1KWGVpnKDfjbrJ4/2LdUnIGL7+sop0mTHBcHqdskpCUwNw9c+kY2A33Dz9SqT2mOK8svTMRQjCszjC2nN7CoSuHdMvJtRhDkQ6XYi6xKGIRQ2sPJW+FKjB2LISFqYyzNqRFuRaU8y9n3E+O4Ndf1Y7ol16CwEDdav5m3dF1nLt5jsG1B6sd4i1aqFDv69d1S8sSA2oNQCCYvSvtxIcG52EMRTr8sOcH4hLjGFl/pHrhxRehQgWVQDA+Xq+4LOAm3BhaZyhrjqzh9PXTuuXYFynVbKJsWfjXv3SruYtZu2ZRwLsAnat0VrOcjz9Wuaf++1/d0rJE6fylaV2+NbN3z8ZOwTc5CWMo0mHOnjnUeqgWtYrVUi94e6t00fv2KXeDDRlSewhJMonZu80ILcusXg1btyoj4WOdaJzouGhCI0LpU70P3h7e6sVGjVSSy08+gZMn9QrMIoNrD+bglYP8eeZP3VJyJcZQpMGxqGP8fvL3+zfYBQVBu3Zqg9WNG1q0ZYcqhavwcOmHmblzphmhZQUp1f992bJqz4KFWBK5hOj4aOV2upN331W6x43TIyyb9ArsRR73PMzaNUu3lFyJMRRpkBKS179m/7vfEAL+7//g6lWYOFGDsuwzrM4w9l3cx1/n/tItxX6sXg1btqibrpeXbjV3MWvXLMr6l+WRso/c/Ua5cipp4Pffq2SXNsPf25/u1bozb8884hPt5/K1O8ZQpMGc3XNoVqYZ5QuUv//NJk3UrOLjj+9LRW4H+tboi5e7FzPDzaJ2ppAS3npLzSaGD9et5i7O3zzPT4d/YlCtQakX1Hr9dVU+NZVU5HZgUK1BXIy5yJoj9gwksTPGUDyA3ed3s/vCbgbWTCOv07hxqubA1KmuE+YgCuYtSPdq3ZmzZ44ZoWWGn35SKcTHjrXcbOKHvT+QKBPvdzul4O+vkhWuXavWV2xGpyqdKJS3ELN2G/eTqzGG4gHM3TMXd+Gedk3sVq2gWTP44AOIi3OdOAcxtPZQLsVcMqmcM0rKbKJMGZXK22J8v+t76peoT/Wi1R/8oVGjoEABW0ZAebl70bd6XxbvX8zNuJu65eQqjKFIBSklc/fMpX2l9jzk+9CDPyiEmlWcPKmyzNqMjpU7UtSnqNlTkVF+/lml6rDgbGL/pf1sO7ONwbUeMJtIwc9PFeMKC4PISNeIcyCDaw8mJj7GbBh1McZQpMLmU5s5FnWMATUHpP/hTp1UsZj331flU22Ep7snA2sNZNmBZVy5dUW3HGtj8dnE7F2zcRNu9wdepMazz6raFR9+6HxhDiZlzdBEP7kWYyhSYc7uOXh7eBMcEJz+h1NmFQcPwoIFzhfnYIbWGUpcYhwL9tpPu0tZswZ+/10tCOfJo1vNXUgpmbV7Fu0qtqOEX4n0T3joIQgJURFQZ844X6ADEUIwqNYgfj7yM+duntMtJ9dgDMU9JCQlMH/ffLpV7Ub+PPkzdlKPHiqFwzvvqJTTNqJe8XpUKVSFhRELdUuxLimzidKl1Q3WYvx+8neORR1L3+10Jy++qBIFfvaZ84Q5iUG1BpEkk0xGWRdiDMU9rDu6jgvRFzLmdkrBzU2NNPfsgWXLnCfOCQgh6F29N+uPrudSzCXdcqzJxo2waZMlZxOg9k74ePrQI7BHxk+qWBH69VP7gKKinCfOCQQWDaRBiQYms4AL0WYohKCMEKwXgggh2CsEz+nScidzds/BP48/nap0ytyJAwaoHFDvvKNGoDaiT/U+JMpEs0D4ID77TFU6tODaRHxiPPP3zSeoWhD5vPJl7uRXXlGZBWyYimZQrUFsO7ON/Zf265biGIQ4hhC7ESIcIbbplnMvOmcUCcCLUhIINAXGCEEacX3O51b8LUIjQukV2Ot/eXIyioeHilH/80/bZZatW7wuFQtWZME+s05xH8eOwZIlKqw0b17dau5jw7ENXLl1hX41+mX+5Lp14bHH4PPPbbdptH/N/ghETltba4OUdZGyoW4h96LNUEjJWSnZkfz3DSACKKVLD8DKgyu5EXeDAbUy4Xa6k2HDoHhx+PRTxwpzMkII+lTvw9oja7kcc1m3HGvx1VcqYOEf/9CtJFUWRSzC19OXDpU6ZK2B115Tm0Zn2itEuoRfCZqVacaiiEW6peQKLLFGIQTlgXrAFp065uyZQzHfYrQp3yZrDeTJA6NHw48/qigoG5HifloSuUS3FOtw86Yq+NO7t1rIthiJSYmE7Q+ja9Wu5PXM4mynVSto3FiFytqsCl6vwF7sPL8zpxQ0ksBPCLEdIUbpFnMv2g2FEOQDFgHPS8l9lVWEEKOEENuEENsSnHgh34y7ycqDK+lboy/u2SlE/+ST4OkJX3/tOHEuoH6J+pQvUN64n+5k5ky4dk3VHrEgv534jQvRF+gV2CvrjQihZhVHjkBoqOPEuYBe1dX3XrTP8rMKj5R7WPKRmiFojpT1gU7AGIRo6WKNaaLVUAiBJ8pIzJaSVK9SKeVkKWVDKWVDDw8Pp2lZdWgVsQmx2fvRgXI99e4N06erEalNSHE/rTmyhqu3ruqWo5+kJPjiC1XLoWlT3WpSZVHEIrw9vDMfeHEvQUEqCuqrrxwjzEWU9S9Lo5KN7OB+Ski5hyUf9xcAl/JM8uMFIAxo7FqJaaMz6kkAU4EIKflEl44UQiNCKepT9P70zFnhmWdU2cnvv89+Wy6kd/XeJCQlGPcTqFTiBw6o2YRFamHfSZJMYlHEIjpV7pT5aKd7cXODp55SYcC7dztGoIvoFdiLP8/8yYlrJ3RLyTpC+CKE399/Qwdgj1ZN96BzRtEcGAI8KgThyUdnHUJuJ9xm+YHlBFULyp7bKYWmTaFBAzVCs1GobKOSjSjnX864n0BFApUoAX3SSAqpkS2ntnDmxpnsz4BTePxxVb3xm28c056LSHE/hUbYy212D8WA3xBiJ7AVWIGUlsrUqTPq6TcpEVJSW0rqJh8rdWhZc2QNN+Ju0DOwp2MaFAKeflqVS12/3jFtuoCUzXc/H/6ZqFh7bcJyKPv3qxnFU09ZLvlfCgv3LcTTzZOuVbs6psHChaF/fzULvn7fUqFlqVyoMrWL1WbhPhtnFpDyCFLWST5qIOU7uiXdi/bFbCsQGhFK/jz5aVuxreMa7d9fFYn58kvHtekCelfvTXxSPEsjl+qWoo8vvlAG4skndStJFSkliyIW0aFSB/y9/R3X8JgxEB0N333nuDZdQK/AXvx+8nfO3jirW0qOJdcbihSffLeq3fByd+Do0dsbnngCli6F48cd166TaVKqCWXyl7H3CC07XL2qop0GDlTJ8yzIjrM7OH7tuOPcTik0bKgW77/5xlYu097VeyORhO0P0y0lx5LrDcXG4xu5fOuy49xOd/LUU+rRRikShBD0CuzF6sOruRZ7Tbcc1zNlCsTEWDYkFpTbycPNg6CAIMc3PmYMRETAhg2Ob9tJVC9anYAiAXaIfrItud5QhEaEktcjL49VeszxjZcpA8HB8O23tkqR0KdGH+IS41h+YLluKa4lKUmNplu2VOktLIiUkoURC2lTvg2F8hZyfAd9+0KhQrbbB9QrsBe/HPuFi9EXdUvJkeRqQ5EkkwjdH0rHyh3x9fJ1TifPPANXrsA8+6REblq6KaX8SuW+6Kc1a1Rup5SZoAXZfWE3h64ccrzbKYW8eWHECFi8GE6fdk4fTqBXYC+TWcCJ5GpDsfX0VseGGKZGq1ZQs6Za1LaJ39dNuNErsBerDq3KXbWJJ09W0T89MpGu28Us2rcIN+GWsaJaWWX0aDW7mnz/vjCrUrd4XSoUqGDcT04iVxuK0IhQPN086VK1i/M6SQmV/esv2KI1lVWm6BHYg9uJt1l9aLVuKa7h3DmVJXb4cEvWnEhhUcQiWpRtQbF8xZzXScWKqsTv5MkQH++8fhxISmj32iNrc3dot5PItYZCSkloRChtK7algHcB53Y2cCD4+qqFUpvwSNlHKJS3EIsjc0mNiunTVVK8UZbLx/Y3+y/tZ+/Fvc6dAacwZowynmH2iSTqFdiL+KR4lkXaq3iYHci1hmL3hd0cvnqYngFOiHa6Fz8/ta9i3jxVKMYGeLh50LVqV1YcWEF8oj1GlVkmKUkFHLRuDVWr6lbzQFKS3zklQu9eHntMFeKy0U7tRqUaUTp/aeN+cgK51lCk+HqdEmKYGk88oTYzzZ3rmv4cQHC1YK7GXmXjiY26pTiXtWvh6FFLzyYAFkcupkmpJpTK74KyLe7uaq3il19UuKwNcBNu9AzoyapDq4iOi9YtJ0eRaw1F6P5QWpRtwUO+LtpU1bgx1KqlRq42oUOlDnh7eOf8Eqk2WMQ+ff00285sI6iaiwY2oNZrPDxg6lTX9ZlNggKCuJ14m58O/6RbSo4iVxqKA5cPsOfCHtdM4VMQQs0qtm2D8HDX9ZsNfL18aV+xPUsilyBtErGVac6fV6Ggw4ap3fQWJSWlistmwKB2pgcFqZQecXGu6zcbtCjbggLeBUyYrIPJlYYiLEIt0Dk1xDA1Bg9WNyMbzSqCA4I5ce0E4efsYdwyzYwZahH7iSd0K0mTJZFLqFyoMoFFAl3b8YgRcPEiLLPHArGnuyddqnRh+YHlJCTZq2KflcmVhmJJ5BLql6hPWf+yru24YEFV1Gj2bJUmwgZ0rdoVgciZI7SUReyWLSEgQLeaB3L99nXWHV1HULUghKtrY3TooMrA2ihiL6haEJdvXeb3k7/rlpJjyHWG4vzN82w+tdm1vt47eeIJVV5zgT12PT/k+xDNyzbPmesU69bB4cOWzRKbwqpDq4hPitdzzbq7Q0iISrt+wh7FgTpW7oiXuxdL9ufAwY0mcp2hWH5gORKpz1C0aKFCMO3kfqoWzM7zOzl69ahuKY5l8mSV16inC9eqssCSyCUU8SlCszLN9Ah4/HH1OH26nv4ziV8eP9pWaJuz19ZcTK4zFEsil1DOvxy1i9XWI0AIGDkSNm1ShY1sQMoCao6qUXH+vNpMZvFF7PjEeFbWnk1iAAAgAElEQVQcWEG3qt0cU30xK5QvD+3bw7RpkJioR0MmCaoWxOGrh9l30R6/MauTqwxFTHwMPx/5me7Vurve13snw4aBp6dt/L6VC1WmRtEaOWuX9nff2WIR+5fjv3Dt9jV9M+AURo5Urqc1a/TqyCDdqnUDyJlraxrIVYbi58M/E5sQq/9Hd2fY4e3berVkkOCAYFW7I+aybinZR0o1Om7WDAJdHEWUSZbsX0Jej7y0r9Rer5Du3VXFRpsMbkr6laRxqcbGUDiIXGUolkQuwT+PPy3LtdQtRY1kL1+2TS6doGpBJMpEVhxcoVtK9tm8WdXFDgnRrSRNpJQsiVxC+0rt8fH00SsmTx4YOlQlTrxwQa+WDBJULejvDNGG7JFrDEViUiLLDyync5XOeLp76pYD7dop369NRmgNSjaglF+pnBH9NHWqStLYt69uJWkSfi6ck9dP6p8BpzBihMom+/33upVkiJR/N5MkMPvkGkOx+dRmLsZctM6Pzs1NjWjXrlXFciyOm3Cje7XurD68mlvx9qnWdx83b8IPPygj4eenW02aLIlcgkDQtWpX3VIU1asrd92UKbaorVK9aHUqFaxk3E8OINcYiiWRS/B086RTlU66pfyPYcNUFNSMGbqVZIjggGBi4mNYc8QeC5qpsnChMhYWdzuBumablWnmunxkGWHECOW2++MP3UrSRQhBULUg1h5dy43b9sjabFVylaFoU6EN+fPk1y3lf5Qtq8IOp09Xu4QtTuvyrcmfJ7+93U/Tpql9LM2b61aSJsejjhN+Ltz1aWbSo29fyJfPNvuAggKCiEuMY9WhVbql2JpcYSj2X9rPgcsH6F61u24p9xMSosIO163TrSRdvNy96FS5E8sPLicxyR7x9Hdx4ABs3Kj+zXWGR2eAv5MAWsVVmkK+fKq2yoIFtqit0qxMMwrnLWzcT9kkVxiKlB9d92oWNBRBQSoH1LRpupVkiKBqQVyIvsDW01t1S8k806erlBRDh+pWki6LIxcTWCSQKoWr6JZyPyEhqraKDdLQ/F2A62AuKMCVGYQoiBAZ3nWcIUMhBEWFYKwQTBaCaSlH1lW6lpQkgGX8y+iWcj/e3jBoEISGwtWrutWkS6cqnfBw87DfLu2EBJg5U9WCLlFCt5o0uXrrKr8c+8V6s4kUmjZVSRRtNLiJio3K+QW40kOIDQiRHyEKATuB6QjxSUZOzeiMYgngD6wBVtxxZAsh6CgEkUJwSAhey257qXH+5nn+OPmHNd1OKYSEqI13Nqh+V8C7AK3KtbLfVH71ajh7Vi3GWpwfD/1Ioky05gwYlNsuJESloYmM1K0mXVIKcFk6SaAQHREiEiEOIYRT7oWAP1JeB3oC05GyAdAuIydm1FD4SMmrUjJfShalHFlVCyAE7sDXQCegOjBACKpnp83U+DsJoCsLvmSWevWgbl3bjNC6V+tOxKUIDl4+qFtKxpk2Te2I79JFt5J0WRK5hGK+xWhSuoluKQ9myBDlxrNBokBfL1/aVWzH0gNLrZkkUIj77oUI4fB7IeCBECWAvsDyzJyYUUOxXAg6Z1pW2jQGDknJESmJA+YBDr+bLz2wlHL+5ahTrI6jm3YsISGwfTvs3KlbSbqkjHRt4366eBGWLlU3N08LbLZMg7jEOH48+CPdqnbDTVh4CbF4cWV0Z85Ubj2LE1QtiGNRx9h9YbduKanRGDiElEeQ0mn3QuA/wGrgMFL+iRAVgQyN9jJ6JT6HMha3hOC6ENwQgutZFJtCKeDkHc9PJb/mMGLiY/j5sAWSAGaEgQPBy8sWI7TyBcpTu1htlh6wiaH4/nt1M7PB3okNxzZwI+6GtWfAKTz+OJw7B6usH3qaUoDLooMbp98LAZByAVLWRsqnkp8fQcpeGTk1Q4ZCSvykxE1K8kpJ/uTn2d2QkNqd+755oRBilBBimxBiW0ImRy6xCbE83/R5BtQckFWNrqNwYQgOhlmzbFGfuHvV7vx24jfrJwlMSQDYtKnaWWxxlkYuxcfTh7YV2uqWkj5duih3ng0GN8XzFadJ6Sa61tY8Uu5hyceoe97P0L0w2whRGiHCEOICQpxHiEUIUTojp6ZpKIQgIPmxfmpHNmWfAu4MQyoN3Je9S0o5WUrZUErZ0MPDI1MdFMpbiHfbvsvDZR7OnlJXERKiEgXaoD5xUEAQSTLJ+kkCt26FvXv/V3zHwkgpWRq5lA6VOpDXM69uOenj6anceUuXKveexeletTvbzmzj9PXTru46IeUelnxMvuf9DN0LHcB0YClQEjVjWZb8WrqkN6P4Z/Ljx3ccH91xZIc/gSpCUEEIvID+qC+Re2nXTtUntsGidv0S9SnpV9KqU/n/MW0a+PioTWIWJyUJoKUj9O7l8ceVW2/WLN1K0iXFnbfsgOUGYn8CVRCiAkI4815YFCmnI2VC8jEDKJqRE9M0FFKSMkWaAARJSRtgPXANeCkbgpGSBOBp1OJKBDBfSvZmp03b4+4Ow4crn+9pl496MoWbcKNb1W6sOrSK2IRY3XJSJzpahRz36QP5LZS65QEsjVxqrSSAGaFGDWjSRGXktWJE0R0EFgmkUsFK1hvcSHnfvRApnXEvvIQQgxHCPfkYDGTId5zRxex/Scl1IXgEaA/MQBmPbCElK6WkqpRUkpJ3sttejmD4cJX3aeZM3UrSJahaENHx0aw/ul63lNRZuFClmbDB3gn4XxLAor4ZGuRZh5AQ5d7btk23kjSxdJJAKVciZVWkrISUzroXhqBCY88BZ4HeQIZ8shk1FCmJfboAE6VkCeCVSZGGjFCpErRurUZoFk8U2KZCG3w9fa03Qkth2jSoUgUeeUS3knQ5ee0kf537y7q7sdOiXz/Im9cWLtPu1boTlxjHT4d/0i1FB28Dw5CyKFI+hDIc4zNyYkYNxWkhmISyRiuFIE8mzjVklpEj4cgR+OUX3UrSxNvDm8cqP8bSA0tJkhYzagcPwq+/2iIBIFg8H1l6+PtD794wZw7ExOhWkybNyzanUN5C9sss4BhqI+X/8gRJeQWol5ETM3qz74vyn3WUkiigEPByJkUaMkrPnurHN3WqbiXpElQtiDM3zrDj7A7dUu5m2jS15jNsmG4lGWLpgaVUK1yNakWq6ZaSNR5/HK5fh0XZStjgdDzcPOhSpQsrDq4gIcn6GwUdjBtCFPz7mcr5lKFQ0ozuo4iRklAp1S4+KTkrJbly7uYS8uZViQIXLrR8osDOVTrjJtyslUfHRgkAAa7FXmP90fX2nE2k0KqVcpvaZHBz5dYVNp3YpFuKq/kY+B0h3kaI/wC/Ax9k5ETjPrIqI0aoRIFz5uhWkiZFfIrwSNlHrLVLe9Uq2yQABFh9eDXxSfH2XJ9Iwc1N/Xv/8ouq+2FhOlTqgJe7V+5zP0n5HdALOA9cBHoiZYYKoBtDYVXq11fJAm0wQutetTu7zu/iWNQx3VIUU6faJgEgqGinoj5FaVq6qW4p2WPYMOXus/iitl8eP9pWaMvSSIsmCXQmUu5Dyq+Q8kuk3JfR04yhsDIjRsBff8EOi/n/7yFlI5Ml3E/nz8Py5ao4kcUTAALEJ8az8uBKulbtirubu2452aNkSWWcZ8yAeGsXCeperTuHrx5m38UM3ytzNcZQWJmBAyFPHsvPKioXqkzNh2oStj9Mt5T/JQC0idtp44mNRMVG2Xt94k5GjlTGeoW1U7t0q9oNsFEGZM0YQ2FlChaEXr1g9my4dUu3mjQJrhbMxhMbuRRzSZ8IKZVRbdZMVWCzAUsjl+Lt4U37iu11S3EMnTqpmcWUKbqVpEmp/KVoWLJh7lunyCLGUFidkSPh2jVVKtXCBAcEkySTWH4gU/VQHMvmzbB/vy3SiYNKArh4/2LaVWyHr5evbjmOwcNDhcr++COcOqVbTZoEVQtiy+ktnL1xVrcUy2MMhdVp1QoqVrS8+6l+ifqUyV9Gr/tpyhTw9YW+ffVpyATh58I5fu04PQJ66JbiWEJCVFaBGTN0K0mT4IBgADOryADGUFgdNzf1w1u/Hg4f1q3mgQghCA4I5qfDPxEdF+16Adeuwbx5MGAA+Pm5vv8sELY/7O/kijmKihWhbVvLp6GpUbQGlQtVtsbamsUxhsIODB+uDIbFww6DA4KJTYjVk0dn1iyVPuLJJ13fdxYJjQilRdkW9ksCmBFGjoRjx2DdOt1KHogQgh4BPVh3dB1RsVG65VgaYyjsQKlSapFw+nRLhx22LNeSgt4FXT9CkxImTYIGDaBhQ9f2nUUOXj7I3ot7c57bKYXgYChUyPKL2j0CepCQlMCKA9aO0tKNMRR2YdQotdvYwtXvPNw86FatG8sPLCc+0YUGbfNm2L3bVrOJFGPaIzCHGgpvb1X9LiwMLmmMhEuHJqWbUCJfCUL3WztYRDfGUNiFzp1V9bsJ2S4D4lR6BPTgauxVNp7Y6LpOJ05U6xIDbFAbPZmw/WE0KNGAsv5ldUtxHiNGqPrvFq5+5ybcCA4IZtWhVdyKt3YIuk6MobALHh5qVrFmjUqhbVE6VOpAXo+8hEW4yP109SrMn6+SKObL55o+s8mZG2fYfGpzznU7pVCrlqp+N3mypavf9QjoQUx8TG6tUZEhjKGwEyNHKoMxaZJuJQ/Ex9OHDpU6sDhysWvy6Hz3HcTGwujRzu/LQaSkOsmxbqc7efJJiIiwdG2V1uVbU8C7gIl+SgNjKOxEiRJqkXD6dEvv1O4R0INT1085v0ZFyiJ2kyZQp45z+3IgYfvDqFq4KoFFAnVLcT79+6tF7a+/1q3kgXi6e9KtajeWRi517dqajTCGwm489RRcuQILFuhW8kC6Vu2Km3Bz/ght40Y1WrXRIvbVW1dZf2w9PQJ6IGxQeS/b5M2r9gGFhcHp07rVPJCUtbVfj/+qW4olMYbCbrRpA9WqWXpRu7BPYVqWa8ni/Yud29GkSaoSYL9+zu3HgSw/sJyEpIScvz5xJ6NHq413336rW8kDeazyY2ptzbifUsUYCrshhPrhbd4M4eG61TyQHgE92HtxLwcvO2nh/dIlVQFw6FDw8XFOH04gbH8YJf1K0qhUI91SXEelStCxo1rUtug+IB9PHx6r/BiL9y+2Xv13C2AMhR0ZNkxN6S08q0ip1ua0WcWMGSr00kZup5j4GFYdWkVwtWDcRC776Y0Zo/YBhVl3xN4zoCenb5xm25ltuqVYjlx2teYQChZUi4SzZ6uC9hakXIFy1CtezzlTeSnV6PSRR6BGDce37yR+OvwTtxJu5Y5op3vp2BEqVLD0onbXql3xcPMgNMJsvrsXYyjsylNPQXS0KtRjUXpX780fp/7g5LWTjm147Vq1l8RGswlQbqeC3gVpVa6Vbimux91dXbO//qp20VuQgnkL0rp8a8L2h+W+EqnpYAyFXWnUSOU2mjDBspuZ+lTvA8DCfQsd2/Cnn0KxYtCnj2PbdSLxifEsjVxKt2rd8HS3folWpxASoio2fvONbiUPpEdADw5cPkDEpQjdUiyFMRR2ZvRo2LsXfvtNt5JUqVK4CvWK12P+vvmOazQiAlauVD7vPHkc166T+eX4L0TFRuWuaKd7KVxYuUy//96yLtOUGhUuyyxgE7QYCiH4UAj2C8EuIQgTggI6dNieAQNUeOiXX+pW8kD61ujL5lObOR513DENfv65MhA22okNMH/vfPJ55aNDpQ66pehlzBjlMv3uO91KUqWkX0malm7KwggHz4KzihDjEeI0QoQnH511yNA1o/gZqCkltYEDwOuadNgbX191w1y0CI4c0a0mVfrWUNXmFuxzwAbBS5dg5kyVlbSofWo4xCfGsyhiEd2rdcfH0z6hvE6hUSN1fPONZV2m/Wr0I/xcOJGXInVLSeFTpKybfKzUIUCLoZCSn6QkIfnpZqC0Dh05gmefVQuFn36qW0mqVCxYkYYlGzJ/rwPcT5MmqbxOzz+f/bZcyJoja7hy6wr9a/TXLcUajBmjXIjr1+tWkip9qvdBIPhh7w+6pVgGK6xRhAA/6hZhW0qWVJlTp02Dy5d1q0mVvtX78ueZPzl69WjWG7l9G776Ch57zFYhsQDz9s6jgHcB43ZKoV8/NSP8+GPdSlKlVP5StCzXkrl75lol+ulphNiFENMQoqAOAU4zFEKwRgj2pHIE3fGZcUACMPvB7YhRQohtQohtCQkJD/pY7ubFF1UZUItuwOtTQ0UnZcv99MMPcO4cvPCCg1S5htiEWMIiwugR0IM8HvZZfHcq3t7w3HMqKGHXLt1qUqV/zf7sv7Sf3RccEsrrkXIPSz5G3fWuEGsQYk8qRxAwAagE1AXOAlqsq9BlMYVgGDAaaCslMRk5x9fXV0ZHRztXmF3p3Bm2b4fjx9UP0WI0mdKEhKQEto/anvmTpYT69dVO7D17VBoTmxAWEUbP+T1ZPXi1mVHcydWrULYsdO+uNo5ajIvRFynxcQleaf4K77Z9N1ttCSFipJS+2RYlRHlgOVLWzHZbmURX1FNH4FWge0aNhCEdXnoJLlywbDWxvtX7suPsDg5dOZT5kzdsUHmtXnjBVkYC4Ie9P1DEpwiPVnhUtxRrUbCg2jA5b54lAzGK+halXcV2zNszT6/7SYgSdzzrAezRIUPXGsVXgB/wsxCEC8FETTpyDm3aqFH3Rx+pTJ0W42/3094suJ8+/RSKFFFrMTYiOi6aZQeW0TuwNx5uHrrlWI8XXlCBGBZdq+hfsz9Ho47y55k/dcr4ACF2I8QuoA2gxfeqK+qpspSUkZK6yYe9guKtiBBqVhEZCStW6FZzH2X9y/Jw6Yczv/nuwAFYtgz+8Q+VCNFGLDuwjJj4GPrXNNFOqVKqlMr+O20anD+vW819BAcE4+Xuxbw98/SJkHIIUtZCytpI2R0pz+qQYYWoJ4Oj6NNH+X0//FC3klTpW6Mv4efCOXD5QMZP+vxz8PJShsJm/LD3B0r6leSRso/olmJdXn5ZRbR98YVuJfdRwLsAnSp34oe9P+T61OPGUOQkPDzUdH7jRtiyRbea++hdvTdAxvdUnDmjRpuDB6vcTjbiWuw1Vh5cSZ/qfXB3c9ctx7pUqwY9e6qsshZM69G/Zn/O3DjDbyesmSbHVRhDkdMYMQIKFFBrFRajdP7SNC/TPOOG4t13ISEBxo1zrjAnsHj/YuIS44zbKSO8+ipcu6Y2VFqMblW74ePpo9f9ZAGMochp+PmptB6hocq/bzH61ujL7gu7ibiYTnbO48dVzYkRI6BiRdeIcyDz9s6jnH85mpRqoluK9WnUCNq2VUELt2/rVnMXvl6+dKvajQX7FpCQlHv3cRlDkRN54QVVHvRf/9Kt5D56V++NQDB3z9y0P/j222qB3oaziUsxl1hzZA39a/ZH2CycVxuvvaYq4Fmwvkr/mv25FHOJtUfW6paiDWMociIPPaR2ay9YAH9qDe27j5J+JWlfqT0zd8588ALhoUOq1Ono0VCmjEv1OYLQiFASkhLoV6Ofbin2oW1bVV/lgw+Uu9FCdKzckfx58jNvb+51PxlDkVN58UWVT+e11yyXpTOkbggnrp1g3dF1qX/grbdUpNPr9kwqPG/PPKoWrkrd4nV1S7EPKbPHgwdh+nTdau7C28ObnoE9CY0I5XaCtVxjrsIYipyKn59yPa1bBz//rFvNXQQFBFHAuwDTw1O5Iezbp1I6PPMMFC/uenHZ5MS1E2w4toH+NYzbKdMEB0Pz5uq6vXFDt5q76F+jP9dvX2fVoVW6pWjBGIqczJNPQvnyalZhod3a3h7eDKw5kNCIUKJio+5+8803VZ2Nl1/WIy6bTP9LGb/H6z2uWYkNEQI++USlovnvf3WruYtHKzzK802ep1KhSrqlaMEYipxMnjzwf/8Hf/0F8x1YjtQBPF7vcWITYu8OOwwPh4UL1WJ8kSL6xGWRxKREpoVPo13FdpQvUF63HHvSuDEMHKjSepw8qVvN33i6e/Jpx0+p+ZDL8/FZAmMocjoDBkCdOmo6HxenW83fNCjRgJoP1bzb/fTvf6s9IP/8pz5h2WDNkTWcuHaCkfVH6pZib959V62rjR2rW4khGWMocjpubvDee3D4MHz7rW41fyOEIKRuCFtPb2XfxX1qJ/myZcrlVMCeJdSn/DWFwnkLE1QtKP0PGx5MuXJqsDBrFmzbpluNAY31KLKCqUeRRaRU2WUjIpTByJdPtyJA5fwv+UlJ/tnwWf47br2Koz9wQC3E24wL0Rco/Ulpnmn8DB8/Zs1sqLbi+nWoUkWl+PjlF9ull78Th9Wj0IiZUeQGhID331eLhJ98olvN3xT1LUrXql3J99UktY7y1Ve2NBIA3+/8nvikeEbUH6FbSs4gf374z39U3rLFi3WryfWYGUVuom9fWLoUduyA6tV1qwFg7eqJNOv6FFFtmlLipz90y8kSUkqqf1OdQnkLsSlkk245OYeEBLW+FhcHe/eqvTU2xMwoDPbiyy/ViH3oUIiP160GkpJo8+5c4jwE43rac10C4PeTv7P/0n5G1jOL2A7Fw0NFPx06pGabBm0YQ5GbKFZMJdrbvh3eeUe3Gvj2W9x+/ZXVT3Xg+4truBB9QbeiLDHlryn4efn9XcXP4EA6doQuXdSu7b17davJtRhDkdvo0QOGDFH7K3TmgTp1Cl55BR59lJqvfUxCUgKzd83WpyeLXIu9xvy98xlQcwD5vKwRJJDjmDoV/P2hXz+IidGtJldiDEVu5IsvoEQJ5YK6dcv1/UupKtbFx8PkyVR/qAaNSzVmWvg0vYXss8C8PfOIiY8xeyecSbFiKqvs3r1qM6YObt+Gp56y1CZAV2IMRW6kQAGVeG3/fj2bmubPV3sm3n4bKqmUCCPrjWTPhT38evxX1+vJBlP+mkLtYrVpWLKhbik5m/btVSqayZNdn2VASpXJeOJE2LzZtX1bBSmlbQ4fHx9pcCDPPCMlSLlunev6PHpUyqJFpWzYUMr4+L9fjomLkUU/KCq7zO7iOi3Z5K+zf0nGI7/Y/IVuKbmDuDgpmzaVMn9+KQ8fdl2/H3ygfif//neWTgeipQXun9k5zIwiN/P++1C1KgwfrkpROpsLF6BDB+VymjlTRbUkk9czL083fpoVB1eondo2YOK2ieRxz8Og2oN0S8kdeHrC3Lkq28CAAa5JSbN0qSrV2revSliZSzGGIjfj46N8v2fOQOfOzi1uf/06dOqkFrFXrEh1H8eYRmPw8fTho9+tV+/7Xs7eOMuM8BkMrzucQnkL6ZaTeyhfHqZMga1bnV/BMTxcJShs2FAV0nLLvbfL3PvNDYrGjeGHH9QP77HHnDOziI1VtQZ27VLZYZs1S/VjhX0KE1I3hFm7ZnH6+mnH63Agn/zxCfFJ8bzS/BXdUnIfvXqpheUPP1RGwxmcOwfdu0PBgrBkCeTN65x+bIIxFAbo2VPdwLdvV4uGUVHpn5NREhNh0CBYv16Nyjp3TvPj/3z4nyTKRL7Y8oXjNDiYK7euMGHbBAbUHEDFghV1y8mdfPyxGtg88YRyCTkyWu7WLQgKgsuXleupRAnHtW1XdC+SZOYwi9lOZtkyKb28pGzQQMrLl7PfXlKSlE88oRYCP/ssw6f1XdBX5n8vv7wWey37GpzA+PXjJeORu8/v1i0ldxMXJ2VIiLq+hg9Xz7PLxYtSduqk2gwNzX57MmcsZmsXkJnDGAoXsGKFlHnySFm3rpSXLmW9nStXpBwxQl1i48Zl6tQ/T/8pGY/8aNNHWe/fSVyPvS4Lvl9QBs0N0i3FIKUajIwfr66z9u2lvJaNwcWKFVIWK6YGSxMmOEyiMRTZ7Rz5kpozyiIZ+bwxFC5i1SplLKpVk3LBAikTEjJ+bkKClJMmSVm4sJRublK++qr6MWeS1jNay9KflJZxCQ4YJTqQDzd9KBmP3HJqi24phjuZNk1KDw8p69SR8vTpzJ1786aUo0er22GtWlLu3OlQadkyFNBHwl4JSRIa3vPe6xIOSYiU8FiW+7CyoQBZBuRqkMeNobAg69ZJWaWKukSqVVM/xNu30z5n40Yp69VT57Rqla0f3IoDKyTjkd+Ff5flNhzNrfhbsvhHxWW779rplmJIjdWrpcyXT0p/fylHjVLXY3qDlM2b1XUuhJQvvSTlrVsOl5VNQxEooZqEDXcZCqguYaeEPBIqSDgswT3L/aRzaEszLgQLgbeBJUBDKbmU3jkmzbiLSUyERYtUhbzwcChTBl56CRo1UtFR16//73HrVrVjtnRptdDYp0+2is1IKak1oRZuwo2do3ciLFC4ZuK2iTy14inWDV1HmwptdMsxpMaePfDf/0JoqMoLVb48DB6sAio8PdX7e/fe/Vi6tNrX07q1UyQ5JM24EBuAl5ByW/Lz1wGQ8r3k56uB8UjpnFz9zrJAaR0gu4P8PPnvY2ZGYXGSkqRcuVLKFi3UbCG1I29eKd94Q03jHcSMv2ZIxiNXHVzlsDazSnxivCz/WXnZdEpTmZQFV5rBxdy4IeV336l1Cze3+6/XcuWk7NxZ7baOinKqFByxRnH/jOIrCYPveD5VQu9s9/OAwyNtM5J1hGANUDyVt8YBY4EOGWtHjAJGAXjZtHCJ7RFCbZbr1EmF0F68qCqQ+fv/7zFfPodvSBpQawDj1o3j3xv+TftK7XET+qK55+2Zx7GoY3zR8QtLzG4M6ZAvn8qSPGSI2lAaFgbe3lCzptrs6dpKih5CiDuLf0+WUk7++5kQD75XSrnkAW2mdhE6zT3kcteTENQC1gIp+YJLA2eAxlJyLq1zjesp9zFr1yyGhA1hUtdJjGowSouGJJlErQm1cBfuhI8O12qwDPYjJ7ieXH7FS8luKXlISspLSXngFFA/PSNhyJ0MqjWIVuVa8fra17kUk+4yllOYumMq+y7uY2yLscZIGKzCUqA/QuRBiApAFWCrszozV73B0ggh+Lrz11y/fZ3X1rzm8v5PXz/NSz+/RJvybehXo5/L+wxJHykAAA1oSURBVDfkcoTogRCngIeBFckzB5ByLzAf2AesAsYgZaLTZLja9ZQdjOsp9/LyTy/z0R8fsSlkE83KpJ4rytFIKQmaF8SaI2vY/dRuKhWq5JJ+DTkLh7ieNGNmFAZb8GbrNynlV4p/rPgHCUkJLulz/t75LDuwjP979P+MkTDkaoyhMNiCfF75+KzjZ+w8v5Nv/vzG6f1dirnEMz8+Q6OSjXiuyXNO789gsDLGUBhsQ6/AXnSo1IE31r/B2RtnndrXC6tf4GrsVaZ2n4q7m7tT+zIYrI4xFAbbIITgq05fEZsQy0s/v+S0flYeXMmsXbMY+8hYahWr5bR+DAa7YAyFwVZUKVyFV5u/ypzdc5i7e67D279++zqjl4+metHqjG0x1uHtGwx2xGk7sw0GZzG2xVh+Of4LQ8KGkNczL8EBwQ5pN0km8dyq5zh1/RS/j/idPB55HNKuwWB3zIzCYDu8PbxZPmA5DUs2pN/Cfqw+tDrbbSYkJTBi6QhmhM9gbIuxNC3d1AFKDYacgTEUBlvil8ePHwf9SPWi1Qn+IZgNxzZkua3YhFh6z+/NjPAZjG81nrfbvO04oQZDDsD2G+7i4+M5deoUsbGxmlRlH29vb0qXLo2np6duKbbjYvRFWs9szfGo46wZuibTM4Hrt68TPC+Y9cfW80XHL3imyTNOUmpIjZzw+03hQb/jnLDhzvaG4ujRo/j5+VG4cGFbZvWUUnL58mVu3LhBhQoVdMuxJWdvnKXljJZcjL7IumHrqF+ifobOuxh9kU6zOxF+LpwZwTMYXHuwk5Ua7sXuv98U0vod5wRDYXvXU2xsrK0vMiEEhQsXzhEjKl2U8CvB2qFr8ff2p/G3jQmeF8zyA8sfuIP7ZtxNlh9YTssZLdl7cS9h/cKMkdCE3X+/KeT033GOiHrKCReZIXuU9S/LHyP+4IstXzAjfAZLIpdQyq8UIfVCGF53OFduXeGnwz/x0+Gf+P3k78QnxVPQuyCrB6+mZbmWuuXnanLK9Z9Tvkdq2N71FBERQWBgoCZFD2bkyJH885//pHr16hn6vFW/hx2JT4xn2YFlfLvjW1YfWo28o55LveL16FCpAx0qdaBZmWZ4e3hrVGrIadd9at8nJ7iecsSMwopMmTJFt4Rci6e7Jz0De9IzsCcnrp1gwd4FlPArQbuK7XjI9yHd8gwG22H7NQorEB0dTZcuXahTpw41a9bkhx9+oHXr1mzbpopR5cuXj3HjxlGnTh2aNm3K+fPnNSvOPZT1L8uLzV5kYK2BxkgYUuW7776jdu3a1KlThyFDhnD8+HHatm1L7dq1adu2LSdOnABgwYIF1KxZkzp16tCyZe5yV+aoGcXzq54n/Fy4Q9usW7wun3X8LM3PrFq1ipIlS7JixQoArl27xoQJE/5+Pzo6mqZNm/LOO+/wyiuv8O233/Kvf/3LoToNBtvz/PMQ7tjfL3XrwmcP/v3u3buXd955h02bNlGkSBGuXLnCsGHDGDp0KMOGDWPatGk8++yzLF68mP/85z+sXr2aUqVKERUV5VidFsfMKBxArVq1WLNmDa+++iobN27E39//rve9vLzo2rUrAA0aNODYsWMaVBoMhntZt24dvXv3pkiRIgAUKlSIP/74g4EDBwIwZMgQfvvtNwCaN2/O8OHD+fbbb0lMdFoxOUuSo2YU6Y38nUXVqlXZvn07K1eu5PXXX6dDhw53ve/p6fl3RIS7uzsJCa4pvGMw2Io0Rv7OQkqZbrRSyvsTJ05ky5YtrFixgrp16xIeHk7hwoVdIVM7ZkbhAM6cOYOPjw+DBw/mpZdeYseOHbolGQyGDNC2bVvmz5/P5cuXAbhy5QrNmjVj3rx5AMyePZtHHnkEgMOHD9OkSRP+85//UKRIEU6ePKlNt6vJUTMKXezevZuXX34ZNzc3PD09mTBhAi+95Lx6CQaDwTHUqFGDcePG0apVK9zd3alXrx5ffPEFISEhfPjhhxQtWpTp06cD8PLLL3Pw4EGklLRt25Y6depoVu86zD4Ki5BTvofBkBly2nWfU/dRGNeTwWAwGNLEGAqDwWAwpIkxFAaDwWBIkxxhKOy0zpIadtdvMGSHnHL955TvkRq2NxTe3t5cvnzZtv9JKXnsvb1NcjpD7sPuv98Ucvrv2PZRTzmhQpapcGfIreSE328KpsKdMzoWPAM8DSQAK6TklfTOSc1QGAwGg5XJlqEQog8wHggEGiPltuTXywMRQGTyJzcj5ehsSn0gWjbcCUEbIAioLSW3hcCk9TQYDIb72QP0BCal8t5hpKzrChG6dmY/BbwvJbcBpOSCJh0Gg8FgXaSMAEBz9Txdi9lVgRZCsEUIfhGCRpp0GAwGg12pgBB/IcQvCNHCmR05bUYhBGuA4qm8NS6534JAU6ARMF8IKso7a1b+3Y4YBYxKfiqFELeyIMcDtRaSEzHfzZ6Y72ZPsvLd8gohtt3xfLKUcvLfz4R48L1SyiUPaPMsUBYpLyNEA2AxQtRAyuuZ1JYhnGYopKTdg94TgqeA0GTDsFUIkoAiwMX725GTgcn3vp4ZhBDbpJQNs9OGVTHfzZ6Y72ZPnPLdpHzgvTKNc26Dct0j5XaEOIzy1GxL67Ssosv1tBh4FEAIqgJewCVNWgwGg8FeCFEUIdyT/64IVAGOOKs7XYZiGlBRCPYA84BhqbmdDAaDIVcjRA+EOAU8DKxAiNXJ77QEdiHETmAhMBoprzhLhpaoJymJAwa7sMtsua4sjvlu9sR8N3vi2u8mZRgQlsrri4BFrpJhq53ZBoPBYHA9ts/1ZDAYDAbnkqMNhRCioxAiUghxSAjxmm49jkIIUUYIsV4IESGE2CuEeE63JkcjhHAXQvwlhFiuW4sjEUIUEEIsFELsT/7/e1i3JkchhHgh+XrcI4SYK4SwbYY8IcQ0IcQFIcSeO14rJIT4WQhxMPmxoE6NriTHGgqhIgL+v717C7GqiuM4/v3ZdMEsIgLxBplZZqJpF8IhKO2hULQXoQtl4UuUmnQRCyJ6CISiy0MFYRdBK1JMtIsGZhhRUk6mqQ+Vhk5ZRqBIRir+eljr0GlwNjHtOXtm+/+8nH2bff6HOZz/3muv9V8vAjcDY4HbJI2tNqrSHAcesn0ZaSzK/TX6bA0PkGrZ1M0LwDrbY4AJ1OQzShoGzAeusj0OOA24tdqo/pc3gJu6bFsEbLA9GtiQ108JtU0UwDXA97Z32z5K6l01s+KYSmF7v+2OvHyY9GMzrNqoyiNpODANWFJ1LGWSdC6pt8qrALaP2j5YbVSlaiMNLmsDBgI/VxxPj9neBHTtRTQTWJqXlwK3tDSoCtU5UQwD9jWtd1KjH9MGpSqSE4HN1UZSqueBhcCJqgMp2UWkQaWv52a1JZL6dfnpBts/Ac8Ae0mjhg/Z/qjaqEo32PZ+SBdrcOoUM61zojhZFa1adfGSNIjURW6Be2nofqtJmg4csL2l6lh6QRswCXjZ9kTgD2rSfJHb62cCI4GhwNmSWtkFPvSiOieKTmBE0/pw+vGtcFeSTiclieW2V1UdT4nagRmSfiQ1F06RtKzakErTCXTabtz9rSQljjq4Edhj+zfbx4BVwOSKYyrbr5KGAOTXU6bqdZ0TxZfAaEkjJZ1BerC2puKYSiFJpHbuXbafrTqeMtl+1PZw2xeS/mcf267FlantX4B9ki7Nm6YCOysMqUx7gWslDczfz6nU5EF9kzXA7Lw8G+iuYF/tVDUfRa+zfVzSXGA9qQfGa7Z3VBxWWdqBO4HtkrbmbY/Z/qDCmMJ/Mw9Yni9edgP3VBxPKWxvlrQS6CD1yvuafjxCW9JbwPXABUolNJ4AFgPvSJpDSoyzqouwtWJkdgghhEJ1bnoKIYRQgkgUIYQQCkWiCCGEUCgSRQghhEKRKEIIIRSKRBFCCKFQJIrQ7+XS3ffl5aG5P39Z514g6a6C/dMlPVnW+4XQF8U4itDv5cKI7+Xy1mWet400gGyS7ePdHKN8TLvtI2W+fwh9RdxRhDpYDIyStFXSisZkM5LulrRa0lpJeyTNlfRgrtz6haTz83GjJK2TtEXSp5LG5PNOAToaSULSfEk7JW2T9DaA05XWJ8D0Vn/oEFolEkWog0XAD7avAB7psm8ccDtpfpKngCO5cuvnQKNJ6RVgnu0rgYeBl/L2dqC5iu0iYKLt8cC9Tdu/Aq4r7+OE0LfUttZTCNnGPLnTYUmHgLV5+3ZgfC7VPhlYkVqRADgzvw7h34XttpHqNK0GVjdtP0AqrR1CLUWiCHX3V9Pyiab1E6Tv/wDgYL4b6epPoHne52mkGepmAI9Lujw3S52Vjw2hlqLpKdTBYeCcnvxhnvBpj6RZkB5OS5qQd+8CLs7bBwAjbG8kzb53HjAoH3cJ8G3Pww+hb4tEEfo9278Dn+WH2E/34BR3AHMkfQPs4J+51T8k3UFAKlW/TNJ2Ugnt55rmu74BeL+n8YfQ10X32BAKSHoXWGj7u272DwbetD21tZGF0DqRKEIokGejG2x7Uzf7rwaO2d56sv0h1EEkihBCCIXiGUUIIYRCkShCCCEUikQRQgihUCSKEEIIhSJRhBBCKPQ3YuDnuzzDE74AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x23244e835f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "fig = plt.figure()\n",
    "plt.subplots_adjust(top=0.9,bottom=0.15,left=0.15,right=0.85)\n",
    "ax1 = fig.add_subplot(111)\n",
    "\n",
    "t = np.linspace(0,10)\n",
    "y1 = 5*np.sin(t)\n",
    "y2 = 10*np.cos(t)\n",
    "\n",
    "ax1.plot(t,y1,'g',label='sin')\n",
    "ax1.set_xlabel('time(s)')\n",
    "\n",
    "#Make the y-axis label and tick labels match the line color\n",
    "ax1.set_ylabel('sin',color='b')\n",
    "for t1 in ax1.get_yticklabels():\n",
    "    t1.set_color('b')\n",
    "ax1.set_ylim(-6,6)\n",
    "plt.legend(loc=3)\n",
    "\n",
    "ax2 = ax1.twinx()\n",
    "ax2.plot(t,y2,'r',label='cos')\n",
    "ax2.set_ylabel('cos',color='r')\n",
    "for t1 in ax2.get_yticklabels():\n",
    "    t1.set_color('r')\n",
    "ax2.set_ylim(-15,15)\n",
    "\n",
    "plt.legend(loc=4)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<center>图7.11:多y轴图形</center>"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
